Tables of Average Weight and Height of Americans Aged 65 to 94 Years

Mastér, Arthur M.

doi:10.1001/jama.1960.03020070016005

Cited by 144 publications

(56 citation statements)

References 3 publications

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“…Nutritional assessment included body weight and height measurement. Percentage average body weight was then calculated by dividing the patient's body weight by the corresponding age-and sex-specific average body weight [11] and multiplying this ratio by 100. Triceps skin-fold thickness and mid-arm circumference were measured in the right arm midway between the tip of the acromion and the olecranon using a Holtain skin-fold caliper which has a pressure of 10 g/ mm of contact surface area over its entire operating range.…”

Section: Methodsmentioning

confidence: 99%

The Prognostic Significance of Protein-energy Malnutrition in Geriatric Patients

et al. 1995

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SummaryAlthough it has been shown that protein-energy malnutrition is a predictor of adverse outcome in geriatric patients, it is unclear whether this is due to underlying disease or disability, or whether malnutrition is an independent outcome predictor. To clarify the predictive role of malnutrition, we analysed the 4.5-year mortality and living location follow-ups of 219 geriatric patients admitted to a geriatric assessment unit. Prevalence of anthropometric and serological malnutrition indicators were between 13.7% and 39.8% at hospital admission. In bivariate models, prealbumin, subnormal arm muscle area, and subnormal body weight were predictors of mortality and survival at home. On the other hand, albumin, transferrin, and triceps skin-fold thickness did not predict these outcomes. In multivariate models the hazard ratio (HR) of 4.5-year mortality remained significant with an HR of 1.8 (95% CI 1.3-2.6) for subnormal arm muscle area, and 1.6 (95% CI 1.0-2.6) for subnormal body weight. Prealbumin was the strongest serological outcome predictor (multivariate mortality HR 1.9, 95% CI, 1.3-2.8). In these models, subnormal cognitive function, impaired physical function, and creatinine clearance < 30 ml/min were also associated with increased mortality. Malnutrition did not predict hospital discharge location, but among patients discharged home, those with initial malnutrition had a decreased length of survival at home.Our findings indicate that certain protein-energy malnutrition indicators are independent risk factors predicting decreased length of overall survival and survival at home in geriatric patients. Physicians should screen actively for this often unrecognized problem and initiate appropriate treatment strategies.

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Section: Methodsmentioning

confidence: 99%

The Prognostic Significance of Protein-energy Malnutrition in Geriatric Patients

et al. 1995

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“…Standardized techniques were used to collect: triceps and subscapular skinfolds, knee height, weight, mid-arm, wrist and calf circumferences; comparisons were made to accepted references (Master et al, 1960;Frisancho, 1990;Gibson, 1990;Hopkins, 1993). For the geriatric clinic sample, all measures were completed by the research dietitian, excepting weight and height measured at the geriatrician's clinic.…”

Section: Study 1-construct Validationmentioning

confidence: 99%

Validity and reliability of SCREEN II (Seniors in the Community: Risk evaluation for eating and nutrition, Version II)

2005

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Background: Nutrition risk screening for community-living seniors is of great interest in the health arena. However, to be useful, nutrition risk indices need to be valid and reliable. The following three studies describe construct validation, test-retest and interrater reliability of SCREEN II. Methods: Study (1) seniors were recruited from the general community and from a geriatrician's clinic to complete a nutritional assessment and SCREEN II. 193 older adults provided medical and nutritional history, 3 days of dietary recall and anthropometric measurements. A dietitian reviewed all information collected and ranked seniors on risk: 1 (low) to 10 (high risk). Receiver operating characteristic curves were completed. An abbreviated SCREEN II was developed through statistical analysis and expert ranking of the 17 items. Studies (2) and (3) seniors were recruited from the community to self-administer (n ¼ 149) or be interviewed (n ¼ 97) using SCREEN II twice within 2 weeks. For self-administration one index was completed via mail. Interviewer administration was completed via telephone with two interviewers. Intra-class correlations were calculated. Results: (1) Total and abbreviated SCREEN II have increased sensitivity and specificity as compared to SCREEN I in identifying seniors at nutritional risk. (2) Test-retest reliability was adequate (intra-class correlation (ICC) ¼ 0.83). (3) Inter-rater reliability was adequate (ICC ¼ 0.83). Conclusions: SCREEN II appears to be a valid and reliable tool for the identification of risk for impaired nutritional states in community-living older adults, and is an improvement over SCREEN I.

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“…Examining cross-sectional data, Holmgren (1952) came to the paradoxical conclusion that males increased 3.5 cm between the ages of 26 and 70, while females increased 1.3 cm between age 26 and 50 but then declined 1 cm from 50 to 70. Master, Lasser and Beckman (1960) measured older adults between the ages of 65 and 94 in whole inches and found no difference in height with age. Because crosssectional data can be confounded with secular change and selection bias related to age, however, these results are difficult to interpret.…”

Section: Introductionmentioning

confidence: 96%

Age changes in adult stature: trend estimation from mixed longitudinal data

Chandler

Bock

1991

Annals of Human Biology

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Although it is widely accepted that persons become shorter as they grow older, most estimates of the rate of decline are based largely on cross-sectional studies and are confounded by secular changes and individual variation. The present study uses a mixed series of longitudinal physical measurements, obtained by the Busselton Population Studies Group, for nearly the entire adult population of Busselton, Western Australia. All persons in the sample who had a minimum of three measures at 3-year intervals are included in our analysis, regardless of health. Random regressions analysis of the individual height and age data is used to estimate the expected rate of decline of stature with age. A significant sex difference was found, with females declining at a greater rate than males, particularly after the age of 40.

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Tables of Average Weight and Height of Americans Aged 65 to 94 Years

Cited by 144 publications

References 3 publications

The Prognostic Significance of Protein-energy Malnutrition in Geriatric Patients

The Prognostic Significance of Protein-energy Malnutrition in Geriatric Patients

Validity and reliability of SCREEN II (Seniors in the Community: Risk evaluation for eating and nutrition, Version II)

Age changes in adult stature: trend estimation from mixed longitudinal data

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